# Product Team Skills - Claude Code Guidance This guide covers the 5 production-ready product management skills and their Python automation tools. ## Product Skills Overview **Available Skills:** 1. **product-manager-toolkit/** - RICE prioritization, customer interview analysis (2 tools) 2. **agile-product-owner/** - User story generation, sprint planning (1 tool) 3. **product-strategist/** - OKR cascade, strategic planning (1 tool) 4. **ux-researcher-designer/** - Persona generation, user research (1 tool) 5. **ui-design-system/** - Design token generation, component systems (1 tool) **Total Tools:** 6 Python automation tools ## Python Automation Tools ### 1. RICE Prioritizer (`product-manager-toolkit/scripts/rice_prioritizer.py`) **Purpose:** RICE framework implementation for feature prioritization **Formula:** (Reach × Impact × Confidence) / Effort **Features:** - Portfolio analysis (quick wins vs big bets) - Quarterly roadmap generation - Capacity planning (story points or dev days) - CSV input/output for Jira/Linear integration - JSON export for dashboards **Usage:** ```bash # Basic prioritization python product-manager-toolkit/scripts/rice_prioritizer.py features.csv # With capacity planning python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20 # JSON output python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json ``` **CSV Format:** ```csv feature,reach,impact,confidence,effort User Dashboard,500,3,0.8,5 API Rate Limiting,1000,2,0.9,3 Dark Mode,300,1,1.0,2 ``` ### 2. Customer Interview Analyzer (`product-manager-toolkit/scripts/customer_interview_analyzer.py`) **Purpose:** NLP-based interview transcript analysis **Features:** - Pain point extraction with severity scoring - Feature request identification - Sentiment analysis - Theme extraction - Jobs-to-be-done pattern recognition **Usage:** ```bash # Analyze transcript python product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt # JSON output python product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt json ``` ### 3. User Story Generator (`agile-product-owner/scripts/user_story_generator.py`) **Purpose:** INVEST-compliant user story generation **Features:** - Sprint planning with capacity allocation - Epic breakdown into deliverable stories - Acceptance criteria generation - Story point estimation - Priority scoring **Usage:** ```bash # Interactive mode python agile-product-owner/scripts/user_story_generator.py # Sprint planning (30 story points) python agile-product-owner/scripts/user_story_generator.py sprint 30 ``` **Output Format:** ``` US-001: As a user, I want to... Priority: High | Points: 5 Acceptance Criteria: - Given... When... Then... ``` ### 4. OKR Cascade Generator (`product-strategist/scripts/okr_cascade_generator.py`) **Purpose:** Automated OKR hierarchy (company → product → team) **Features:** - Alignment scoring (vertical and horizontal) - Strategy templates (growth, retention, revenue, innovation) - Key result tracking - Progress visualization **Usage:** ```bash # Growth strategy OKRs python product-strategist/scripts/okr_cascade_generator.py growth # Retention strategy python product-strategist/scripts/okr_cascade_generator.py retention ``` ### 5. Persona Generator (`ux-researcher-designer/scripts/persona_generator.py`) **Purpose:** Data-driven persona creation from user research **Features:** - Demographic and psychographic profiling - Goals, pain points, and behavior patterns - User journey mapping integration - Empathy map generation **Usage:** ```bash # Interactive persona creation python ux-researcher-designer/scripts/persona_generator.py # JSON export python ux-researcher-designer/scripts/persona_generator.py --output json ``` ### 6. Design Token Generator (`ui-design-system/scripts/design_token_generator.py`) **Purpose:** Complete design token system from brand color **Features:** - Color palette generation (primary, secondary, neutrals) - Typography scale (font sizes, line heights, weights) - Spacing system (4px/8px grid) - Shadow and elevation tokens - Export formats: CSS, JSON, SCSS **Usage:** ```bash # Generate design tokens python ui-design-system/scripts/design_token_generator.py "#0066CC" modern css # SCSS output python ui-design-system/scripts/design_token_generator.py "#0066CC" modern scss # JSON for Figma integration python ui-design-system/scripts/design_token_generator.py "#0066CC" modern json ``` ## Product Workflows ### Workflow 1: Feature Prioritization ```bash # 1. Collect feature requests cat feature-requests.csv # 2. Run RICE prioritization python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 30 # 3. Generate quarterly roadmap # 4. Create user stories for top priorities python agile-product-owner/scripts/user_story_generator.py sprint 30 ``` ### Workflow 2: User Research to Product ```bash # 1. Conduct user interviews # 2. Analyze transcripts python product-manager-toolkit/scripts/customer_interview_analyzer.py interview-001.txt # 3. Generate personas python ux-researcher-designer/scripts/persona_generator.py # 4. Create OKRs based on insights python product-strategist/scripts/okr_cascade_generator.py growth ``` ### Workflow 3: Sprint Planning ```bash # 1. Set sprint capacity (story points) CAPACITY=30 # 2. Generate user stories python agile-product-owner/scripts/user_story_generator.py sprint $CAPACITY # 3. Export to Jira (via JSON) python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json > priorities.json ``` ## Integration Patterns ### Jira Integration All tools support JSON output for Jira import: ```bash # Export prioritized features python product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json > jira-import.json ``` ### Figma Integration Design tokens export for Figma plugins: ```bash # Generate tokens python ui-design-system/scripts/design_token_generator.py "#0066CC" modern json > design-tokens.json ``` ### Confluence Documentation Use persona generator output for user documentation: ```bash python ux-researcher-designer/scripts/persona_generator.py --output json > personas.json ``` ## Quality Standards **All product Python tools must:** - CLI-first design for automation - Support both interactive and batch modes - JSON output for tool integration - Standard library only (minimal dependencies) - Actionable recommendations ## Roadmap **Current (Phase 1):** 5 skills deployed with 6 tools **Phase 2 (Q1 2026):** Product analytics - A/B test analyzer - Funnel conversion tracker - Cohort retention analyzer **Phase 3 (Q2 2026):** Advanced PM tools - Competitive analysis framework - Product-market fit assessment - Revenue impact calculator See `product_team_implementation_guide.md` for detailed plans. ## Additional Resources - **Implementation Guide:** `product_team_implementation_guide.md` - **Real-World Scenario:** `REAL_WORLD_SCENARIO.md` (if exists) - **Main Documentation:** `../CLAUDE.md` --- **Last Updated:** November 5, 2025 **Skills Deployed:** 5/5 product skills production-ready **Total Tools:** 6 Python automation tools